Spam constitutes a large fraction of the messages that reach and are processed by e-mail services, corporate enterprises, and Internet Service Providers (ISPs). Because of the prevalence of spam, significant portion of the bandwidth and hardware resources of the e-mail services and ISPs are committed to handling and processing spam. At the same time, because spam typically has different properties and is handled differently than ordinary mail, there is an opportunity to optimize the performance of the e-mail servers and other hardware by capitalizing on these particular properties and handling characteristics. More particularly, spam messages tend to be smaller than ordinary mail messages, they are less likely to be read, they tend to be less important or valued by end-users and thus deleted in bulk, and they are typically automatically deleted after a certain period of time (e.g., several days).
In a similar context, corporate enterprises may face similar issues in managing and storing message traffic, such as e-mails. More particularly, such enterprises may be affected not only by spam, but also by a high volume of non-spam messages flowing to and from the persons working within the enterprise. To reduce the volume of such messages that are stored by e-mail servers within the enterprise, administrators may establish policies that mandate that certain classes of messages be deleted automatically after a given period of time. For example, some types or classes of messages may be deleted automatically thirty days after they have been sent or received, regardless of whether they are considered “spam”. In this sense, such classes of non-spam messages may share some characteristics with spam, in that both are retained for defined periods of time and are deleted automatically after expiration of this period of time.
Processing, managing, and deleting a significant number of messages typically entails the message server performing a significant number of input/output (I/O) operations. Such operations are known to involve substantial overhead in preparing hardware, for example disk drives, to actually move the data that may be considered the “payload” of the I/O operations. However, if the processing of such messages is optimized, then the hardware resources committed to supporting such processing may be reduced or consolidated, thereby reducing the overall operational cost borne by ISPs, e-mail service providers, corporate enterprises, or the like. The teachings herein address this and other needs in the art.